A 2D adaptive beamforming method in sparse array

This study presents an Accelerated Proximal Gradient singular value thresholding based Linearly Constrained Singular Canceler (APG-LCSC) algorithm to improve the performance of two-dimensional (2D) adaptive beamforming in sparse array. Firstly, a signal model is established based on Matrix Completion (MC), which can be proved to meet Null Space Property (NSP). Subsequently, left and right singular value vector of the received signal matrix is achieved via MC, and then a linearly constrained singular canceler is obtained by employing the singular value vector. The proposed algorithm decreases the required number of antennas, lowers the computational complexity and has a robust performance. Computer simulations demonstrate that the proposed APG-LCSC algorithm can acquire high accuracy of 2D beamforming in sparse array.